A. Technical Field
The present invention relates to sensor power management, and more particularly, to systems, devices, and methods of integrating electromagnetic and inertial sensors into dynamically managed systems to reduce sensor power consumption.
B. Background of the Invention
There is an increasing trend to integrate multiple sensors, such as accelerometers, gyroscopes, and magnetometers within a single package. Sensors are becoming increasingly inexpensive and have been adopted by the marketplace for use in numerous applications. Accelerometers enable users of consumer electronics to do various tasks in a convenient way, e.g., portraits-landscape conversion or detection of certain events, such as shaking and other movement. Accelerometers typically measure acceleration in one or more dimensions. Spatial acceleration is measured by detecting the difference in three different components about three orthogonal axes, from which angles can be determined. By comparing angles along time, assuming no accelerations other than gravity are present, the angular velocity can then be derived.
Although, in practice, accelerometers provide an absolute reference for gravity, they come with a number of limitations that make them impractical for accurately measuring rotation. Most importantly, accelerometers are not designed to distinguish rotational movement from linear acceleration, because they sense every component of acceleration, including static and dynamic acceleration. Thus, injected lateral movements are perceived by the accelerometer as unwanted disturbances of a rotation based on the difference between angles. Additionally, accelerometers are relatively noisy. As a result, without having additional orientation information, acceleration sensors are not suited for detecting the difference between dynamic and static acceleration.
In contrast, gyroscopes or angular rate sensors are perfectly suited to measure rotation. They are designed to exclusively sense rotational orientation and to reject the disturbances caused by linear acceleration. However, gyroscopes do not possess absolute reference information. Thus, even when an angular rate sensor is motionless and experiences no actual angular rotation, i.e., the RMS value of the estimated rotation angle remains zero, once the inherently noisy output signal of the sensor is integrated with respect to time, the estimated rotation angle will be a nonzero. As a result, a slow angular drift occurs, which can be described by the “random walk” theory.
Existing approaches combine a gyroscope with appropriate, accurate parameters from a low bandwidth accelerometer, to compensate for the slow drift of the gyroscope. However, while accelerometers are able to compensate for the drift of the gyroscope in a pitch & roll plane, they are unable to compensate for drifts around a vertical axis (yaw) of the gyroscope, since the accelerometer lacks an absolute reference for the earth's magnetic North pole. One solution is to add a magnetometer to the combination of gyroscope and accelerometer to compensate for the drift of the gyroscope around the yaw axis, since a magnetometers' magnetic field sensor provides the absolute reference that is lacking from an accelerometer.
However, combining multiple sensors results in a relatively high power consumption which must be sustained by system integrators and which cannot be significantly reduced, especially, as long as the gyroscope is turned on. Today, the average power consumption of a gyroscope available on the market largely exceeds 10 mW. Since the gyroscope is generally a stand-alone object, turning it on or off in real time to manage power requires an application processor that passes data to and from the gyroscope in order to control the gyroscope's turn on and off times. This process is typically managed by software and suffers mainly from two inherent limitations, including time delays and heightened power requirements. Otherwise possible power savings resulting from short-term, e.g. 1 ms, turn off times, are made impractical by the slow timing resolution of software operating systems. Also, power savings resulting from long-term, e.g. 50 ms, turn off times are prevented by the inherently slow turn-on time of the gyroscope. Additionally, software-based approaches require the constant operation of an application processor, for example, to enable data communication to interrogate the accelerometer to determine the proper timing when to turn on and off the gyroscope. This contributes to the increase in data traffic, CPU cycles, and power consumption. Overall, software-based approaches prevent system integrators from achieving significant power savings.
What is needed are methods, devices, and systems that fully integrate sensor power management to overcome the above-mentioned limitations and leverages the superior sensing performance of a gyroscope while reducing gyroscope average power consumption below 5 mW.